Master Thesis: Using machine learning for demand prediction
Master Thesis: Using machine learning for demand prediction (Autumn 2019)
Build upon previous master thesis that was based on historical timeseries data using algorithms such ARIMA and explore alternative methods (e.g. demand curve patterns) and ways to reduce/address the high variance in demand planning data.
Explore suitable methods when limited data is available (possibly including how to use GANs to simulate missing data).
Find patterns in data (external factors, periodical patterns, customers, products etc.)
Propose algorithm that over time learns patterns and identifies risks for delivery disturbances.
Interest in data science, operations research and forecasting. Capacity to code/ compare algorithms by applying them to the data with tools such as R or python. Entrepreneurial mindset and self-learning.
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Primary country and city: Sweden (SE) || || Stockholm || Supply&Log
Req ID: 281035